The companion blog for the book Audience, Relevance, and Search by James Mathewson, Frank Donatone and Cynthia Fishel

PageRank and EdgeRank: How to use Facebook Open Graph to improve search relevance

The key mission of this blog is to extend the book in ways we could not anticipate when we wrote it. We wrote about how Facebook can grow your targeted traffic in two ways: Direct referrals from Facebook and indirect referrals from Google. Though links from Facebook carry the no-follow attribute (meaning they do not carry any link equity in Google), those who share your links improve the likelihood that they will end up in credible blogs that do carry link juice. This improves your ranking in Google, which drives more targeted traffic to your site. You can read more about the force multiplier effect of Facebook and Google in Chapter 8.

But Facebook has changed quite a bit since the copy for our book was locked down. The company released the Open Graph protocol, which extends many of the functions contained within Facebook to your sites, making it easier to integrate your content with Facebook. The other thing that has happened since our copy was locked down is the explosive growth of Facebook. It now is a serious competitor to Google in terms of direct targeted traffic.

Some have even suggested that the two are conflicting tactics to drive targeted traffic to content, and that you should shift SEO efforts to Facebook tactics. We don’t see it that way, so it seems we need to extend the book to make it clear that your Google and Facebook strategies are complementary. Indeed, the force multiplier effect between them is only stronger now than it was in the days before Open Graph. In our book, we recommend using Facebook primarily as a means of gaining link juice in Google. We now see the two as equally important tactics independently, and doubly important together.

The new face of Facebook

Before we talk about how the two strategies correlate, let me say a few things about the new Facebook. Facebook is a content personalization engine. We at IBM have tried to entice our users to sign in and receive content based on some simple survey questions for years. The idea is, if we know who you are and what you care about, we can deliver the content you are more likely to find relevant to you. The problem is, users are notoriously shy about telling us who they are and signing in, no matter how easy we make it. Somehow, Facebook has given users enough enticements to reveal some of their most intimate details and preferences. And now they are making that information public to the world.

Using Open Graph, we now can deliver more relevant content to Facebook users based on their public profiles. In our book, we talk about listening to the nomenclature of your target audience in search and social media, and writing with that nomenclature to deliver more relevant content to them. Facebook extends that concept: Now we can not only know their language use, we can know what that language use represents–their interests and preferences. The challenge of delivering content to users that appeals to their interests is far greater than it was when we contented ourselves with throwing content against the wall and hoping our users liked it. But the challenge is not optional. So let’s start thinking about meeting that challenge.

Posting Like buttons on your content

The most important aspect of Open Graph is the new ability for site owners to post Like buttons next to pieces of content. Prior to Open Graph, you could easily allow users to share your content on Facebook from within your pages. And of course you could create fan pages on Facebook around your topics. Now you can bring the fan experience to your pages. When users indicate that they like your content, that becomes part of their profiles. You can build spaces on your site that include profile pictures and likes to profiles of users who clicked the Like button. (See the Facebook developer page for information on how to do this.)

The main benefit of this is to connect like-minded users of your content together on Facebook, where the viral nature of content sharing is accelerated. The other benefit is it is no longer as important to build fan pages on Facebook itself. It is still a good practice to build these pages if you own persistent topics to which to develop a loyal following. But you now can replicate this experience for smaller modules of content and short-term events on your site. That gives you a lot more flexibility in how you connect to users within their Facebook profiles. If a users clicks the Like button, all her friends will see that. If it happens to be something they too are interested in, they too will like that experience, perhaps within their News feed or at your site. Like buttons can also drive engagement to your content. Users will be more likely to click a link if they see that their friends like it.

In addition to driving more targeted traffic to your content, seeing who likes your content and looking at their profiles is a great way to learn more about your audience so that you can develop ever more relevant experiences for them.

EdgeRank

It’s one thing to put Like buttons on your content, it’s quite another to optimize them. Ever wonder why certain posts in your Facebook News feed hang around the top of the page? The reason is called EdgeRank. EdgeRank is a tacit acknowledgment that you are not equally connected with all your friends. Some are marginal, others are close. That closeness is called affinity. Facebook engineers try to get the posts from your closer friends at the top of your News feed and your marginal friends below. There is a formula for determining what it thinks will be more relevant to you in your News feed. It’s represented here:

An edge is a piece of content. The affinity score is between you and the creator of the edge. If you send a lot of messages to a person, like, share and comment on their posts, and otherwise engage regularly with them, you will have a relatively high affinity score with that person. So, all things considered, that person’s posts will appear higher up on your News feed. The weight is just what it says: A post gets more weight if it’s created than if the person merely commented on it, etc. And finally, EdgeRank for posts tends to decay with age. I often click the Most Recent button at the top of my News feed if I keep seeing the same thing from the usual suspects. But a lot of users can’t be bothered with this and live with the default feed–Top News.

EdgeRank is important because people with higher affinity are more apt to see that like-minded users clicked the Like button next to certain content. So EdgeRank increases the relevance of content to the target audience by automating the targeting. Some of this happens naturally. Two users who find the same piece of content relevant will tend to have higher affinity.

How does EdgeRank affect PageRank?

Before Open Graph, the likelihood that a piece of content would get passed around and commented on in Facebook enough to inspire someone to include it in a blog post was pretty small. We still recommended it as perhaps the best way to increase the PageRank of your content. But you needed a lot of fans to get a little link juice. Now, you can get more link juice with fewer fans because the fans (those who click the Like button) you get will tend to have a higher affinity to one another. This affinity increases the likelihood that one of these fans will include a link to your content in a credible blog post. Affinity is strongly correlated to trust. Bloggers tend to link to sources they most trust. Affinity is a great way to build that trust.

Of course, the usual proviso about having link bait in the first place applies. There’s no substitute for authoritative content. EdgeRank and PageRank are just tactics to increase the visibility of your authoritative content. The good news is, using the Open Graph Like button, you can get them working together to better target your audience with relevant content.